Project Abstract

Abstract
In recent years, the need for sustainable energy management solutions in residential buildings has become increasingly important due to the rising costs of energy consumption and the environmental impact associated with traditional energy sources. This research project focuses on the design and implementation of a smart energy management system for residential buildings to optimize energy usage, reduce waste, and promote energy efficiency. The proposed system integrates advanced technologies such as Internet of Things (IoT), data analytics, and machine learning algorithms to monitor, control, and optimize energy consumption in real-time. Chapter 1 introduces the research topic by providing an overview of the current challenges in energy management in residential buildings and the need for innovative solutions. The background of the study highlights the significance of energy management systems in reducing energy costs, enhancing sustainability, and minimizing the environmental footprint of buildings. The problem statement identifies the key issues related to energy consumption in residential buildings, such as inefficient use of energy resources and lack of real-time monitoring capabilities. The objectives of the study are outlined to address these challenges by developing a smart energy management system that can optimize energy usage, reduce waste, and improve overall energy efficiency. Chapter 2 presents a comprehensive literature review on existing energy management systems, smart technologies, and IoT applications in residential buildings. The review explores the current state-of-the-art solutions, identifies gaps in the literature, and provides a theoretical foundation for the proposed smart energy management system. Key issues such as energy monitoring, load scheduling, demand response, and user behavior analysis are discussed to inform the design and implementation of the system. Chapter 3 outlines the research methodology employed in the development of the smart energy management system. The methodology includes system design, hardware and software implementation, data collection, analysis, and evaluation. Various components of the system, such as sensors, actuators, communication protocols, and data analytics algorithms, are described in detail. The methodology also includes a case study to demonstrate the effectiveness of the system in a real-world residential building environment. Chapter 4 presents the findings of the research project, including the performance evaluation of the smart energy management system in terms of energy savings, user comfort, and system reliability. The discussion highlights the key features and benefits of the system, as well as the challenges and limitations encountered during the implementation process. Recommendations for future improvements and extensions of the system are also provided based on the research findings. Chapter 5 concludes the research by summarizing the key findings, contributions, and implications of the study. The conclusion highlights the significance of the smart energy management system in promoting sustainable energy practices in residential buildings and suggests potential areas for further research and development. Overall, this research project contributes to the advancement of energy management technologies and provides valuable insights for policymakers, building owners, and energy professionals seeking to improve energy efficiency and sustainability in residential buildings. Keywords Smart energy management system, residential buildings, energy efficiency, IoT, data analytics, sustainability, real-time monitoring, machine learning, energy optimization.

Project Overview